The purpose of this study is to present results about the variability of temperature extremes: warm days (tx90), warm nights (tn90), cold days (tx10), cold nights (tn10), cold wave duration index (cwdi) and heat wave duration index (hwdi) for different seasons December-January-February (DJF), March-April-June (MAM), June-July-August (JJA) and September-October-November (SON) over Europe. One important motivation to perform this study is the greater vulnerability of ecosystems to climate extremes than to mean climate changes. The extreme indices are based on threshold exceedance. We use the daily gridded datasets derived through interpolation of station data (E-OBS) version 2.0 (Hofstra et al. 2009). The variability of the indices would be described by using probability density function (PDF), Singular Spectral Analysis (SSA) and different procedures to derive the significance of the trend. The changes in the temperature extreme indices are explained taken into account the atmospheric teleconnection indices and Sea Surface Temperature (SST) variability modes and by means of correlation analysis and composite maps of large-scale variables for the most extreme values of the indices. We will discuss results for the four seasons and provide more additional details with respect to a previous study where temperature extremes of annual time series were analyzed over the Iberian Peninsula (Rodriguez-Puebla et al. 2010). Statistical models are proposed to characterize the temperature extreme indices to be applied in further studies about climate change conditions and to learn how slow climate changes would affect the variability of temperature extremes.